from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 36.0 | 12.691177 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 27.063909 |
| KNeighborsClassifier_kd_tree | 0.0 | 2.0 | 42.927908 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 0.0 | 32.575493 |
| KMeans_tall | 0.0 | 0.0 | 24.670078 |
| daal4py_KMeans_tall | 0.0 | 0.0 | 9.769130 |
| KMeans_short | 0.0 | 0.0 | 3.673587 |
| daal4py_KMeans_short | 0.0 | 0.0 | 1.896952 |
| LogisticRegression | 0.0 | 0.0 | 25.947497 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 4.999089 |
| Ridge | 0.0 | 0.0 | 11.359283 |
| daal4py_Ridge | 0.0 | 0.0 | 2.270106 |
| HistGradientBoostingClassifier | 0.0 | 5.0 | 3.405937 |
| lightgbm | 0.0 | 5.0 | 11.772575 |
| xgboost | 0.0 | 5.0 | 10.147203 |
| catboost | 0.0 | 5.0 | 2.831722 |
| total | 1.0 | 6.0 | 48.109077 |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.316 | 0.000 | 2.535 | 0.000 | 1 | 100 | NaN | NaN | 0.490 | 0.000 | 0.643 | 0.000 | See | See |
| 1 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 25.194 | 0.199 | 0.000 | 0.025 | 1 | 100 | 0.936 | 0.713 | 3.895 | 0.044 | 6.469 | 0.089 | See | See |
| 2 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.196 | 0.003 | 0.000 | 0.196 | 1 | 100 | 1.000 | 1.000 | 0.104 | 0.002 | 1.886 | 0.044 | See | See |
| 3 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.125 | 0.000 | 6.422 | 0.000 | -1 | 5 | NaN | NaN | 0.486 | 0.000 | 0.256 | 0.000 | See | See |
| 4 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 37.710 | 0.000 | 0.000 | 0.038 | -1 | 5 | 0.820 | 0.812 | 3.846 | 0.042 | 9.804 | 0.108 | See | See |
| 5 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.195 | 0.010 | 0.000 | 0.195 | -1 | 5 | 1.000 | 1.000 | 0.105 | 0.002 | 1.857 | 0.103 | See | See |
| 6 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.135 | 0.000 | 5.906 | 0.000 | 1 | 1 | NaN | NaN | 0.472 | 0.000 | 0.287 | 0.000 | See | See |
| 7 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 15.469 | 0.124 | 0.000 | 0.015 | 1 | 1 | 0.706 | 0.934 | 3.946 | 0.066 | 3.920 | 0.073 | See | See |
| 8 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.193 | 0.006 | 0.000 | 0.193 | 1 | 1 | 1.000 | 1.000 | 0.103 | 0.002 | 1.877 | 0.070 | See | See |
| 9 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.125 | 0.000 | 6.426 | 0.000 | 1 | 5 | NaN | NaN | 0.468 | 0.000 | 0.266 | 0.000 | See | See |
| 10 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 24.773 | 0.209 | 0.000 | 0.025 | 1 | 5 | 0.820 | 0.812 | 3.863 | 0.057 | 6.413 | 0.109 | See | See |
| 11 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.199 | 0.008 | 0.000 | 0.199 | 1 | 5 | 1.000 | 1.000 | 0.103 | 0.005 | 1.934 | 0.112 | See | See |
| 12 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.123 | 0.000 | 6.496 | 0.000 | -1 | 100 | NaN | NaN | 0.459 | 0.000 | 0.268 | 0.000 | See | See |
| 13 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 38.197 | 0.000 | 0.000 | 0.038 | -1 | 100 | 0.936 | 0.713 | 3.879 | 0.053 | 9.847 | 0.134 | See | See |
| 14 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.197 | 0.014 | 0.000 | 0.197 | -1 | 100 | 1.000 | 1.000 | 0.105 | 0.002 | 1.882 | 0.137 | See | See |
| 15 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.121 | 0.000 | 6.586 | 0.000 | -1 | 1 | NaN | NaN | 0.474 | 0.000 | 0.256 | 0.000 | See | See |
| 16 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 28.817 | 0.144 | 0.000 | 0.029 | -1 | 1 | 0.706 | 0.934 | 3.990 | 0.051 | 7.223 | 0.100 | See | See |
| 17 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.183 | 0.011 | 0.000 | 0.183 | -1 | 1 | 1.000 | 1.000 | 0.106 | 0.006 | 1.732 | 0.142 | See | See |
| 18 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.058 | 0.000 | 0.277 | 0.000 | 1 | 100 | NaN | NaN | 0.106 | 0.000 | 0.546 | 0.000 | See | See |
| 19 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 19.854 | 0.212 | 0.000 | 0.020 | 1 | 100 | 0.985 | 0.970 | 0.820 | 0.010 | 24.203 | 0.397 | See | See |
| 20 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 100 | 1.000 | 1.000 | 0.005 | 0.001 | 4.875 | 0.901 | See | See |
| 21 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.055 | 0.000 | 0.291 | 0.000 | -1 | 5 | NaN | NaN | 0.106 | 0.000 | 0.517 | 0.000 | See | See |
| 22 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 32.773 | 0.000 | 0.000 | 0.033 | -1 | 5 | 0.983 | 0.978 | 0.821 | 0.011 | 39.936 | 0.518 | See | See |
| 23 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.031 | 0.002 | 0.000 | 0.031 | -1 | 5 | 1.000 | 1.000 | 0.004 | 0.000 | 7.038 | 0.557 | See | See |
| 24 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.057 | 0.000 | 0.282 | 0.000 | 1 | 1 | NaN | NaN | 0.107 | 0.000 | 0.529 | 0.000 | See | See |
| 25 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 10.852 | 0.065 | 0.000 | 0.011 | 1 | 1 | 0.979 | 0.981 | 0.878 | 0.009 | 12.359 | 0.145 | See | See |
| 26 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.016 | 0.001 | 0.000 | 0.016 | 1 | 1 | 1.000 | 1.000 | 0.004 | 0.000 | 3.716 | 0.194 | See | See |
| 27 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.055 | 0.000 | 0.289 | 0.000 | 1 | 5 | NaN | NaN | 0.117 | 0.000 | 0.474 | 0.000 | See | See |
| 28 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 19.707 | 0.247 | 0.000 | 0.020 | 1 | 5 | 0.983 | 0.978 | 0.821 | 0.014 | 24.010 | 0.517 | See | See |
| 29 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 5 | 1.000 | 1.000 | 0.004 | 0.000 | 5.599 | 0.473 | See | See |
| 30 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.053 | 0.000 | 0.305 | 0.000 | -1 | 100 | NaN | NaN | 0.104 | 0.000 | 0.507 | 0.000 | See | See |
| 31 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 32.375 | 0.000 | 0.000 | 0.032 | -1 | 100 | 0.985 | 0.970 | 0.817 | 0.009 | 39.620 | 0.423 | See | See |
| 32 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.030 | 0.002 | 0.000 | 0.030 | -1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 6.367 | 0.493 | See | See |
| 33 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.057 | 0.000 | 0.280 | 0.000 | -1 | 1 | NaN | NaN | 0.110 | 0.000 | 0.521 | 0.000 | See | See |
| 34 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 23.788 | 0.132 | 0.000 | 0.024 | -1 | 1 | 0.979 | 0.981 | 0.884 | 0.011 | 26.921 | 0.357 | See | See |
| 35 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.020 | 0.001 | 0.000 | 0.020 | -1 | 1 | 1.000 | 1.000 | 0.004 | 0.000 | 4.548 | 0.373 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.903 | 0.000 | 0.028 | 0.000 | 1 | 5 | NaN | NaN | 0.760 | 0.000 | 3.818 | 0.000 | See | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 1.501 | 0.027 | 0.000 | 0.002 | 1 | 5 | 0.977 | 0.978 | 0.682 | 0.016 | 2.202 | 0.064 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 2.460 | 0.922 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.835 | 0.000 | 0.028 | 0.000 | -1 | 1 | NaN | NaN | 0.772 | 0.000 | 3.671 | 0.000 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.463 | 0.011 | 0.000 | 0.000 | -1 | 1 | 0.965 | 0.966 | 0.128 | 0.004 | 3.604 | 0.131 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.004 | 0.001 | 0.000 | 0.004 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 15.288 | 7.164 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.920 | 0.000 | 0.027 | 0.000 | 1 | 1 | NaN | NaN | 0.738 | 0.000 | 3.960 | 0.000 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.801 | 0.020 | 0.000 | 0.001 | 1 | 1 | 0.965 | 0.982 | 0.229 | 0.007 | 3.501 | 0.136 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 4.435 | 1.982 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.931 | 0.000 | 0.027 | 0.000 | 1 | 100 | NaN | NaN | 0.781 | 0.000 | 3.756 | 0.000 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 4.954 | 0.084 | 0.000 | 0.005 | 1 | 100 | 0.979 | 0.978 | 0.679 | 0.013 | 7.297 | 0.185 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 1.000 | 1.000 | 0.001 | 0.000 | 4.641 | 2.181 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.753 | 0.000 | 0.029 | 0.000 | -1 | 5 | NaN | NaN | 0.688 | 0.000 | 4.002 | 0.000 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.854 | 0.019 | 0.000 | 0.001 | -1 | 5 | 0.977 | 0.982 | 0.224 | 0.006 | 3.818 | 0.127 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.004 | 0.001 | 0.000 | 0.004 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 15.125 | 6.904 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.815 | 0.000 | 0.028 | 0.000 | -1 | 100 | NaN | NaN | 0.700 | 0.000 | 4.023 | 0.000 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 2.758 | 0.041 | 0.000 | 0.003 | -1 | 100 | 0.979 | 0.966 | 0.124 | 0.002 | 22.242 | 0.535 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 24.824 | 10.787 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.797 | 0.000 | 0.020 | 0.000 | 1 | 5 | NaN | NaN | 0.476 | 0.000 | 1.677 | 0.000 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.037 | 0.001 | 0.000 | 0.000 | 1 | 5 | 0.978 | 0.990 | 0.008 | 0.001 | 4.857 | 0.502 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 5.234 | 2.207 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.813 | 0.000 | 0.020 | 0.000 | -1 | 1 | NaN | NaN | 0.499 | 0.000 | 1.630 | 0.000 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.037 | 0.003 | 0.000 | 0.000 | -1 | 1 | 0.973 | 0.971 | 0.001 | 0.000 | 47.296 | 12.658 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 18.030 | 8.645 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.789 | 0.000 | 0.020 | 0.000 | 1 | 1 | NaN | NaN | 0.544 | 0.000 | 1.452 | 0.000 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.036 | 0.003 | 0.000 | 0.000 | 1 | 1 | 0.973 | 0.989 | 0.001 | 0.000 | 31.531 | 6.348 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 4.479 | 2.000 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.775 | 0.000 | 0.021 | 0.000 | 1 | 100 | NaN | NaN | 0.525 | 0.000 | 1.476 | 0.000 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.062 | 0.003 | 0.000 | 0.000 | 1 | 100 | 0.980 | 0.990 | 0.007 | 0.001 | 8.343 | 1.563 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.001 | 2.001 | 3.113 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.721 | 0.000 | 0.022 | 0.000 | -1 | 5 | NaN | NaN | 0.484 | 0.000 | 1.490 | 0.000 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.038 | 0.003 | 0.000 | 0.000 | -1 | 5 | 0.978 | 0.989 | 0.001 | 0.000 | 33.715 | 7.795 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 16.188 | 7.516 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.726 | 0.000 | 0.022 | 0.000 | -1 | 100 | NaN | NaN | 0.489 | 0.000 | 1.484 | 0.000 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.056 | 0.005 | 0.000 | 0.000 | -1 | 100 | 0.980 | 0.971 | 0.001 | 0.001 | 48.225 | 41.493 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 13.891 | 5.802 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.762 | 0.000 | 0.630 | 0.000 | k-means++ | NaN | 30 | NaN | 0.324 | 0.0 | 2.348 | 0.000 | See | See |
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.002 | 0.001 | 0.251 | 0.000 | k-means++ | 0.001 | 30 | 0.001 | 0.000 | 0.0 | 9.277 | 5.714 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.002 | 0.000 | 0.000 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 8.931 | 3.876 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.553 | 0.000 | 0.867 | 0.000 | random | NaN | 30 | NaN | 0.277 | 0.0 | 1.996 | 0.000 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.002 | 0.000 | 0.311 | 0.000 | random | 0.001 | 30 | 0.000 | 0.000 | 0.0 | 7.012 | 2.465 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.001 | 0.000 | 0.000 | 0.001 | random | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 9.039 | 3.791 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 7.479 | 0.000 | 3.209 | 0.000 | k-means++ | NaN | 30 | NaN | 3.847 | 0.0 | 1.944 | 0.000 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.000 | 13.537 | 0.000 | k-means++ | 0.002 | 30 | 0.002 | 0.000 | 0.0 | 6.210 | 1.952 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.002 | 0.000 | 0.015 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 9.328 | 3.824 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 6.649 | 0.000 | 3.610 | 0.000 | random | NaN | 30 | NaN | 3.587 | 0.0 | 1.854 | 0.000 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.000 | 13.026 | 0.000 | random | 0.002 | 30 | 0.002 | 0.000 | 0.0 | 6.029 | 1.955 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.001 | 0.000 | 0.016 | 0.001 | random | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 8.130 | 3.252 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 20 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.092 | 0.0 | 0.035 | 0.000 | random | NaN | 20 | NaN | 0.134 | 0.0 | 0.689 | 0.000 | See | See |
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.156 | 0.000 | random | -0.001 | 20 | -0.000 | 0.001 | 0.0 | 3.300 | 0.833 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.002 | 0.0 | 0.000 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 7.778 | 3.100 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.303 | 0.0 | 0.011 | 0.000 | k-means++ | NaN | 20 | NaN | 0.047 | 0.0 | 6.451 | 0.000 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.148 | 0.000 | k-means++ | -0.001 | 20 | -0.000 | 0.001 | 0.0 | 3.202 | 0.877 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.002 | 0.0 | 0.000 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 9.087 | 4.093 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 0.316 | 0.0 | 0.506 | 0.000 | random | NaN | 20 | NaN | 0.604 | 0.0 | 0.524 | 0.000 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.003 | 0.0 | 4.757 | 0.000 | random | 0.321 | 20 | 0.319 | 0.002 | 0.0 | 2.116 | 0.697 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.002 | 0.0 | 0.009 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.638 | 3.872 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 1.113 | 0.0 | 0.144 | 0.000 | k-means++ | NaN | 20 | NaN | 0.250 | 0.0 | 4.462 | 0.000 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.003 | 0.0 | 5.183 | 0.000 | k-means++ | 0.326 | 20 | 0.300 | 0.001 | 0.0 | 2.138 | 0.225 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.002 | 0.0 | 0.009 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.061 | 2.882 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | [20] | 15.930 | 0.0 | [-0.07406812] | 0.000 | NaN | NaN | NaN | NaN | NaN | 2.677 | 0.0 | 5.951 | 0.000 | See | See |
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | [20] | 0.000 | 0.0 | [47.78599994] | 0.000 | NaN | NaN | NaN | NaN | 0.554 | 0.000 | 0.0 | 0.911 | 0.281 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | [20] | 0.000 | 0.0 | [0.18191824] | 0.000 | NaN | NaN | NaN | NaN | 1.000 | 0.000 | 0.0 | 0.341 | 0.222 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | [27] | 1.242 | 0.0 | [-1.71898079] | 0.001 | NaN | NaN | NaN | NaN | NaN | 0.911 | 0.0 | 1.363 | 0.000 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | [27] | 0.002 | 0.0 | [93.80609638] | 0.000 | NaN | NaN | NaN | NaN | 0.250 | 0.004 | 0.0 | 0.592 | 0.077 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | [27] | 0.000 | 0.0 | [17.71913691] | 0.000 | NaN | NaN | NaN | NaN | 0.000 | 0.001 | 0.0 | 0.158 | 0.069 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | deprecated |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | NaN | 0.281 | 0.000 | 0.284 | 0.0 | NaN | NaN | NaN | 0.279 | 0.000 | 1.008 | 0.000 | See | See |
| 1 | Ridge | predict | 1000 | 1000 | 10000 | NaN | 0.011 | 0.001 | 7.134 | 0.0 | NaN | NaN | 0.119 | 0.021 | 0.005 | 0.543 | 0.131 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | NaN | 0.000 | 0.000 | 0.613 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.862 | 0.627 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | NaN | 1.440 | 0.000 | 0.555 | 0.0 | NaN | NaN | NaN | 0.345 | 0.000 | 4.177 | 0.000 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | NaN | 0.000 | 0.000 | 4.428 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.000 | 0.755 | 0.380 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | NaN | 0.000 | 0.000 | 0.009 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.658 | 0.531 | See | See |
{
"system_info": {
"python": "3.8.10 | packaged by conda-forge | (default, May 11 2021, 07:01:05) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1047-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1.2",
"setuptools": "49.6.0.post20210108",
"sklearn": "1.0.dev0",
"numpy": "1.20.3",
"scipy": "1.6.3",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": "3.4.2",
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.15.so",
"prefix": "libopenblas",
"user_api": "blas",
"internal_api": "openblas",
"version": "0.3.15",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/python3.8/site-packages/scikit_learn.libs/libgomp-f7e03b3e.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
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}
],
"cpu_count": 2
}